Water stress mapping in crops and its spatial disparity study at field scale is important for precise management of irrigation. Results obtained from conventional airborne practice (balloons, airplanes, and satellites) are less acceptable for timely irrigation management due to lack in spatial and temporal resolutions. Unmanned Aerial Vehicle (UAV) equipped with multispectral (MS) and thermal cameras with higher spectral and temporal resolutions can be used as a promising tool for preparing water stress maps under different water deficit conditions. In this study, Water Deficit Index (WDI) maps are generated at different days after sowing (DAS) in wheat crops under three different water conditions (WI (well water), WS1(irrigation at 5 days’ interval), and WS2 (irrigation at 11 days’ interval)) using the concept of Vegetation Index Trapezoid (VIT) using UAV based thermal and MS imageries. The UAV is flown at 60m altitude during the Rabi season 2018-19. After pre-processing of images in Pix4dMapper, nine vegetation indices are calculated from MS images and one of the indices, Normalized Green Red Difference Index (NGRDI) is selected based on the higher correlation with ground truth data (R² greater than 0.5) and visual interpretation according to the real field condition to construct the VIT. Vegetation index and temperature values are calculated for four points of VIT by using four boundary conditions such as bare soil with (1) dry and (2) wet conditions, and full vegetation with (3) well-watered and (4) water stress conditions. By using the ArcGIS, geo-referencing of thermal images with respect to MS images is done to get the exact overlap of both images, and resampling of thermal and MS images are also carried out to get the same pixel size. WDI values are estimated using VIT of the surface-air temperature difference and NGRDI, and WDI maps are generated from the UAV-based thermal and MS imageries for potential detection of crop water stress. The conventional Crop Water Stress Index (CWSI) which is solely based on the crop canopy temperature is outperformed by the WDI, which is integration of composite land surface temperature (LST) and degree of greenness, and could be effective enough for irrigation water management. Keywords: UAV, Multispectral and Thermal imageries, NGRDI, WDI, and Wheat crop.